This disclosure relates generally to imaging methods and systems, and more particularly to medical diagnostic imaging methods and systems that acquire and process tissue information for measuring the visceral adipose tissue (VAT) of a subject.
Characteristics of a subject, such as body weight, fat mass, height, girth, gender, age, etc. are clinical descriptors useful by physicians to predict certain health risks that may increase or decrease mortality and morbidity risk. For example, the amount or type of abdominal fat, such as subcutaneous adipose tissue (SAT) or subcutaneous fat and VAT or visceral fat are associated with, and useful predictors of, an adverse metabolic risk profile and certain diseases, such as coronary heart disease, diabetes and stroke. In addition, measuring visceral fat, for example, can relate to metabolic syndrome (i.e., a combination of medical problems that can increase the risk of heart disease, diabetes and/or stroke). People suffering from metabolic syndrome can have some or all of the following: high blood glucose, high blood pressure, abdominal obesity, low high-density lipoprotein (HDL) cholesterol, high low-density lipoprotein (LDL) cholesterol, high total cholesterol and/or high triglycerides.
Conventional methods and systems for measuring VAT are mostly performed using anthropomorphic gauges, bioimpedance gauges, weight scales, etc. These devices often are not capable of providing accurate measurements of VAT because the actual fat content is not being measured, certain assumptions and/or estimates are made during the calculation process, and/or the devices are not exactly calibrated. Also, reproducibility may be difficult, leading to inaccurate comparisons between examinations.
Medical diagnostic imaging systems, such as computed tomography (CT) imaging systems or magnetic resonance (MR) imaging systems have also been used to measure VAT content. However, the use of these systems is often very costly and can expose a subject to high levels of ionizing radiation, for example, when using a CT imaging system. Additionally, these imaging systems are not always available for clinical use and may have long scan times. Moreover, certain measurements are inaccurate in larger subjects.
More sophisticated methods and systems for determining VAT often use simple models to approximate the abdominal volume of a subject from an estimate of subcutaneous fat thickness measurements. However, these methods and systems often fail to accurately estimate SAT, thereby resulting in an inaccurate estimate of VAT. For example, a normal dual-energy X-ray absorptiometry (DXA) image of the abdomen is a planar two-dimensional (2D) image that cannot explicitly measure VAT because it cannot measure the thickness of SAT in the vertical plane. It has been very difficult to determine the thickness of the subcutaneous fat region around the abdomen, especially near the buttocks, since the models used in the past do not take into account differences in the thickness of the subcutaneous fat region around the abdomen near the buttocks.
Prior methods and systems for measuring or estimating VAT have subtracted an estimated SAT contribution from the total fat (SAT and VAT) of the entire abdominal region of interest of a subject. However, there are regions of SAT within the entire abdominal region of interest of a subject that are unnecessary in the estimation or calculation of VAT of the subject. The method and system of the present disclosure accurately determines the outer transverse extent of the coelom or inner abdominal cavity and subtracts an estimated SAT contribution from the total fat (SAT and VAT) of only the regions directly anterior (above) and posterior (below) the coelom. SAT beyond the coelom or inner abdominal cavity may be excluded from the estimated VAT calculation. This improves the VAT estimate by eliminating the unneeded outer boundaries of SAT. Furthermore, a new inferior posterior model eliminates reliance on an elliptical model for the SAT outer boundaries, which are known to be inaccurate due to deviations due to buttock fat and flattening of a subject from lying on a table during the method and system of the present disclosure.
Therefore, there is a need for a method and system to more accurately estimate VAT by restricting subtraction of SAT from the total fat (SAT and VAT) to only the coelom in the abdominal region of interest of a subject, and use of a non-elliptical inferior posterior model that eliminates reliance on an elliptical model for the SAT outer boundaries, which are known to be inaccurate due to differences of fat in the superior and inferior sections in the abdominal region of interest of a subject.